class_docstr: Apply transforms according to the condition. If the condition is met,
  true_transforms will be applied, otherwise false_transforms will be
  applied.
  
  Args:
      condition (str): The string that can be evaluated to a boolean value.
      true_transforms (list[dict]): Transforms to be applied if the condition
          is met. Defaults to [].
      false_transforms (list[dict]): Transforms to be applied if the
          condition is not met. Defaults to [].
code: def __init__(
      self,
      condition: str,
      true_transforms: Union[Dict, List[Dict]] = [],
      false_transforms: Union[Dict, List[Dict]] = [],
  ):
      self.condition = condition
      self.true_transforms = Compose(true_transforms)
      self.false_transforms = Compose(false_transforms)
  
imports: import warnings
  from typing import Any, Dict, List, Optional, Tuple, Union
  import imgaug
  import imgaug.augmenters
  import numpy
  import torchvision.transforms
  from mmcv.transforms import Compose
  from mmcv.transforms.base import BaseTransform
  from PIL import Image
  from mmocr.registry import TRANSFORMS
  from mmocr.utils import poly2bbox
label_desc: Use image node_id 1 to create a new ConditionApply object from inherited base classes: BaseTransform with example: obj = ConditionApply(condition, true_transforms, false_transforms)